Computerized Decision Support System for Aircraft Repair Efficacy
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Solution Overview
Problem
Complex systems, such as aircraft, often require maintenance and repair, but accurate feedback on corrective actions is often lacking due to workload pressure and human nature, leading to inefficiencies and increased maintenance costs.
Innovation Solution
A system comprising a network, local computing devices, and a reasoner that collects and correlates failure mode data, repair action data, and operating status to infer and update the success probability of repair actions, providing inferred feedback to improve repair efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If accurate maintainer feedback is collected to improve diagnostic accuracy, then diagnostic accuracy improves, but workload pressure and human nature cause feedback to be unavailable
Solution Approach 1:
The system implements automatic feedback collection by monitoring system state transitions before and after repair actions. The reasoner component analyzes whether the system transitioned from a failed state to an operational state, automatically generating feedback about repair effectiveness without requiring manual input from maintainers.
Solution Approach 2:
The system performs self-assessment of repair effectiveness by automatically comparing system operational status before and after repair actions. The computerized decision support system monitors its own performance and generates efficacy data without external intervention, eliminating the reliance on maintainer feedback.
2Measurement precision
If more isolation tests and repair procedures are performed to identify failure modes, then repair accuracy improves, but maintenance time and costs increase
Solution Approach 1:
The system pre-calculates and stores multiple isolation tests and repair procedures in a database before they are needed. When a failure occurs, the computerized decision support system automatically retrieves and executes the most appropriate pre-prepared procedures based on the casualty code, eliminating the need for maintainers to manually plan and sequence multiple tests.
Solution Approach 2:
The system replaces the mechanical process of manual test selection and execution with an automated computerized decision support system. The reasoner component automatically determines which isolation tests to perform and which repair procedures to execute, reducing maintenance time while maintaining or improving accuracy.
3Reliability
If computerized decision support system provides repair guidance, then repair accuracy improves, but system complexity increases
Solution Approach 1:
The computerized decision support system is designed to handle multiple failure modes and repair scenarios through a single unified platform. The system can manage ambiguity groups, perform isolation tests, execute repair procedures, and collect efficacy data across different system components, reducing the need for multiple specialized tools while improving repair reliability.
Data Source
AI summary
Methods and systems are provided for improving the repair efficacy of a repair action using inferred feedback. The method comprises downloading a repair procedure, which has a probability of success for correcting the fault code. Repair action data is input into to the computing device and is tracked and correlated with the downloaded procedure. The method then adjusts a probability of success of the repair procedure in clearing the fault code generated by the complex system based at least on the correlation. The system comprises a means for receiving repair data, a means for tracking repair action data taken, a means for correlating the tracked repair action and the repair data, and a means for updating a probability of success of the repair action based at least in part on the correlation of the repair data, the repair action data and the operating status of the complex system.